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The Moth Flame Optimization (MFO) algorithm is a member of the swarm intelligence family that is utilized to tackle complex optimization problems in various real-world domains. MFO, along with its different variations, offers simplicity in understanding and ease of operation. These algorithms have exhibited great success in solving optimization problems across diverse fields such as power and energy systems, engineering design, economic dispatch, image processing, and medical applications. This comprehensive review explores the different variants of MFO, encompassing the classic version, binary types, modified versions, hybrid versions, multi-objective versions, and the application aspect of the MFO algorithm in different sectors. Furthermore, the evaluation of the MFO algorithm is presented to assess its performance relative to other algorithms. The primary focus of this literature is to provide a survey and analysis of MFO and its applications. Additionally, the concluding remarks section delves into potential future research directions for the MFO algorithm and its variants.
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